Various color systems (U.S. Pat. No. 6,281,984 B1) are used for color specification in image processing and image reproduction (for example on a monitor or a printer). While input devices (for example scanners) predominantly designate colors via RGB, knowledge of the area coverage degree of the primary colors (mostly CMYK) is necessary for color reproduction devices. However, other color reproduction devices such as monitors also use RGB for color specification.
This problem is explained using FIG. 1. An original image BV is, for example, shown in a first color system (for example RGB) with a scanner SC. The RGB image values for the original image BV are, for example, translated into CIE-LAB image values. The original image should now be output by a color reproduction device, a printer as an example. The printer operates in a second color system, for example CMYK. The CIE-LAB color values are correspondingly translated into the color system CMYK. The printer WG can now print the original image as BV′.
All of these color specifications are device-dependent, i.e., for example, the same RGB values of two different scanners or scanner and monitor, describe different colors. This device dependency has been known for a long time. In order to enable a correct color communication between the various devices, a conversion of the device-dependent color specification into a device-independent color system (for example CIELAB) is therefore frequently effected. For this conversion, the color values are typically determined with a color measurement device and associated with the device-dependent color specification (RGB, CMYK). One possibility of such a color association is the creation of tables, as this is implemented in the color profiles according to the ICC International COLOR Consortium (address: www.Color.org). Such color profiles are also specified in DE 199 46 585 A1. However, it is just as conceivable to use functions instead of tables to specify the color association. Color association is discussed in the following for a conversion rule of color specifications, for example between device color specification and an arbitrary color specification (for example CIELAB).
What is problematic is that color reproduction devices can in principle not cover the optimal color space, but rather are limited to more or less sizable color ranges. Therefore colors that are not reproducible by the color reproduction device are modified in the color conversion. There are various possibilities for this color adaptation. This, for example, given color management according to ICC, four variants of the color association tables are already established by default. For the most part it is attempted to obtain an optimally similar image impression given color images; this color adaptation is called “perceptual” in ICC. Not only are the colors that are not achieved by the respective color reproduction device thereby changed, but rather also those colors lie in the boundary range of the achievable color space. This is necessary in order to obtain a gradation between various colors.
FIG. 2 shows these relationships. Shown there in an xy-graphic (as a part of ClExyY) over the color norm portion x, y is the theoretical optimal maximal color space FR (unbroken curve) and the color space FR-WG (dot-dash curve) achievable by a color reproduction device, for example a printer. Colors are additionally specified as an example. When the color space achievable by an original image is greater than the color space achievable by an original image, a color space adaptation occurs (shown by unbroken arrows). The colors outside of the color space of the color reproduction device are thereby shifted into the color space of the color reproduction device. This compression occurs for all colors lying outside of the color space of the color reproduction device, but also for colors lying within the color space of the color reproduction device in order to obtain the color gradation explained above.
Many methods of color space adaptation are known. A few examples are found in                the IS&T Proceedings of the Eighth Color Imaging Conference, 2000-11-07 through 2000-11-10 in USA, Arizona, Phoenix, Scottsdale, SunBurst Hotel.        L. MacDonald, J. Morovic, K. Xiado: Topographic Gamut Mapping Algorithm Based on Experimental Observer Data; IS&T Proceedings of the Eighth Color Imaging. Conference, 2000-1107 through 2000-11-10 in USA, Arizona, Phoenix, Scottsdale, SunBurst Hotel        H. Motomura: Gamut Mapping Using Color-Categorical Weighting Method, IS&T Proceedings, Eighth Color Imaging Conference, 2000-11-07, Scottsdale.        
In the known methods, such a color association for each created image is independent for each color reproduction device. This means that all theoretically possible colors must be mapped in the color space of the color reproduction device. However, this also leads to colors that lie within the reproducible color space having to be significantly changed and reduced in terms of their saturation. Given images that do not completely cover this theoretical optimal color space, this leads to an unnecessary modification of the colors of the image. As a rule, given color images only a limited color space is necessary, such that most images are unnecessarily significantly changed.
The conversion of color information ensures that color specifications exist that can be traced over the entire color transfer process. This color value conversion thereby must be determined for each individual device (or device class) and also for different transfer settings (brightness setting on the monitor, paper grade in the printer, etc.). According to methods typical today, this is implemented one time for each device state used.